ProjetFinal

Projet final

This visualization shows a network of music artists, with nodes connected by association rules derived from item-set support values. It presents a force-directed graph where each circle represents an artist, and links indicate shared listener preferences or recommendations between them, with node size and link strength reflecting the support counts. The implementation uses D3 v4’s `d3.forceSimulation` for layout, rendering nodes and links as SVG circles and lines. Hovering highlights a node, dims unrelated connections, and displays a tooltip with the artist’s name and support value, based on data from CSV files containing artist tags and recommendation counts.

95% match

Projet 2

This visualization shows a force-directed network of music artists and their associations, mapping relationships derived from an association-rule mining dataset where nodes represent artists and links indicate co-occurrence strength. The graph uses `d3.forceSimulation` with collision and link forces to position nodes, with circle size encoding node degree and line opacity reflecting link weight. Hovering a node highlights its connections, and the code includes an autocomplete search feature that filters the network. Data is loaded from CSV files containing artist tags and recommendation pairs, rendered as SVG elements with tooltips for interactivity.

90% match

Projet final

This network graph shows music artist recommendations derived from association rule mining. Each node is an artist, and a directed edge connects an antecedent to a consequence. The thickness of a link encodes the support count for that rule, as seen in the `recommandations.csv` file. Artists are colored or sized by tag counts from `artists_tags_count.csv`. The visualization uses D3.js v4's force-directed layout to position nodes, with SVG paths and circles rendering the links and nodes. Hovering on a node triggers a brush effect that highlights connected nodes while dimming the rest.

90% match

Projet final

This example visualizes a network of music artist recommendations derived from an association-rule mining dataset, showing how often one artist appears alongside another. A force-directed graph positions nodes for each artist, with links representing recommendation strengths encoded by line opacity and weight. The interface includes a searchable auto-suggest input to highlight a selected artist and dim unrelated nodes, using D3 v4’s `forceSimulation` for layout and SVG circles and lines for rendering. Data comes from CSV files containing artist tags and item-set support counts, with tooltips providing context.

RRomyRatolojanahary

90% match

Projet 4

This visualization displays a network of recommended music artists based on association rule mining. The force-directed graph shows artist nodes connected by links, where the strength of each connection represents the support value from the dataset. Using D3 v4, the layout employs a force simulation to position nodes, with link opacity reflecting relationship strength. The data comes from a CSV file containing antecedent-consequence pairs with support counts, and the interactive visualization also includes a searchable autocomplete feature for finding specific artists in the network.

Projet_test2

This example shows a network of music artists and their associations, using a force-directed graph layout to reveal clusters of related performers. The visualization encodes connections through links and nodes, with the ability to hover and search for a specific artist. The code relies on `d3.forceSimulation` with `d3.forceLink` and `d3.forceManyBody` to compute the layout, and uses custom SVG elements for nodes and links. Data is loaded from two CSV files, `recommandations.csv` and `artists_tags_count.csv`, with node size reflecting artist popularity and a tooltip displaying tag information.

Projet 4

This network visualization maps music artist recommendations, showing associations between bands and solo acts. It displays artists as nodes, with connections and support values indicating the strength of their association. The visualization uses a force-directed simulation, `d3.forceSimulation` in the D3.js framework, to position nodes and draw links between them. Data is loaded from `recommandations.csv`, which includes the antecedent, consequence, and item-set support for each recommendation pair. The visualization also includes an interactive autocomplete feature for searching artists.

Projet final

This force-directed graph visualizes music artist recommendations derived from association-rule mining on a Last.fm-style dataset. Nodes represent artists, while links show recommendation strength, with thicker connections indicating higher co-occurrence support. The visualization is built with d3.v4, using `d3.forceSimulation` for layout and SVG circles and lines for rendering. Hovering a node highlights its immediate connections and applies a semi-transparent “retrait” effect to unrelated nodes, while a custom tooltip shows each artist’s name. Data comes from the included `recommandations.csv` and `artists_tags_count.csv` files.

RRomyRatolojanahary